Car Thefts in Washington DC

Introduction

Starting in 2022, a breakout social media trend started the rise of a troubling trend: teenagers stealing cars for fun. The trend, started by the alleged “Kia Boys,” spread on the social media platform TikTok, where teenage boys posted videos of themselves stealing cars to take them on joyrides (Arango and Fortin 2023). Often, these videos included step-by-step instructions on how to steal a car, and many of the cars stolen were Kia and Hyundai models. Videos show an easy trick that that involves just a screw driver and a USB cord to start the car in less than a minute due to a software error (Manjoo 2023). In Figure 1, we see a significant increase in Google searches for “Kia Boys”, “Hyundai Theft”, and “Kia Theft” starting in 2022 and continuing through today (2024).

Figure 1: Searchs for Kia Thefts, Hyundai Thefts, and Kia Boys in the U.S. increase from 2020 to 2024, indicating that the Kia Boys trend is contributing to real car thefts. Source: Google Trends

This trend in Hyundais and Kias being stolen is not quite new, however. According to the Highway Loss Data Institute, theft insurance claims for certain models of Hyundais and Kias have increased more than 1000% between the first half of 2020 and first half of 2023. During the initial six months of 2020, approximately 1.0 per 1,000 insured Hyundai and Kia vehicles were reported stolen, a rate similar to that of other car brands. However, by the first half of 2023, this rate surged to 11.2 per 1,000 for Hyundai and Kia vehicles, while the theft rate for other car brands remained the same.The “epidemic” of thefts of these brands has gotten so bad that Hyundai recently reached settled a class action lawsuit for $145 million, with any one who purchased a Hyundai between 2011 and 2022 being eligible to be compensated (Valdes-Dapena 2024).

Figure 2: As the number of Kia and Hyundai thefts increase in U.S. cities from 2019-2023, the percentage of Kia and Hyundai increases as well, indicating a potential trend in car thefts. Source: VICE NEWS Kia and Hyundai Theft Data

With this problem of Hyundai and Kia thefts, we became curious as to how not only how this epidemic is impacting our own home in Washington DC, but also if we can visualize DC car theft data to identify any notable patterns, trends, or insights as to how car theft typically manifests itself in our city. To accomplish this goal, we take a look at car thefts as a whole in the United States, Hyundai and Kia thefts in DC and also various cities throughout the United States, and crime report data from the DC Metro. It is through exploring all these various avenues that we can see how DC stacks up against other cities/the country as a whole with car thefts and answer important questions like where in DC are the most cars getting stolen, who is stealing cars, and most importantly, why?

Where Are These Crimes Being Committed

Figure 3: From 2019-2023, the Kias and Hyundais are stolen at an increasing rate, showing the negative impact of the Kia Boys trend on the car theft rate in the US. Source: VICE NEWS Kia and Hyundai Theft Data

Looking at Hyundai and Kia theft in the US on a broader scale, we can visualize the epidemic of these vehicles being stolen in Figure 3. Over time, from 2020 to 2023, it is very clear that the proportion of vehicles stolen in major cities throughout the US have become increasingly Kia or Hyundai. This visualization shows us how DC is one of the major hubs for Kias and Hyundai thefts in the US.

Seeing how DC stacked up nationally to other cities in the US with respect to car thefts, we wanted to take a closer look at not just car theft data in DC, but also all reported crime and arrests in the city. It is through such an exploration that we can begin to paint the picture for how the criminal landscape in DC operates.

In Figure 4, the proportion of types of crimes and where they were committed in DC can be visualized.

Figure 4: This Sankey diagram shows the relationship between motor vehicle thefts and other crimes in each ward, highlighting the prevalence of motor vehicle thefts across DC.

We can first observe how theft that was NOT from vehicles made up most of the crime in Washington DC from 2019 through 2023. Theft is then followed by theft from vehicles, and then third by motor vehicle thefts (the act of physically stealing a vehicle). For the most part, crime in DC is interspersed evenly throughout the district’s wards, but we can see that Wards 2, 5, and 1 are where most crimes in happen in the city. While certain wards do not seem inherently more dangerous than others (relatively speaking), can we see if motor vehicle thefts happen more often in particular wards? In order to answer this question, let us first take a look at motor vehicle theft trends as a whole in the city.

Figure 5: Car thefts increase each year in Washington DC between 2019 and 2023. Source: Open Data DC Crime Incidents 2019-2023.

Looking at yearly counts of motor vehicle theft in DC, we can see that there has been a VERY clear rise in car thefts overall, not just in Hyundai and Kia thefts. Clearly there is problem in DC. From 2022 to 2023, there was an almost 82% increase in car thefts which is staggeringly high. In Figure 6 and Figure 7, we can see how many of these thefts are happening in DC’s 7th and 8th wards, the southeast of the city. Historically, this area of the city has long been one of the most economically disadvantaged areas in the city, with 16th Street NW being a “dividing line” for poverty within the city (Paul 2013).

data_df = transpose(grouped_crimes)

dc = FileAttachment("../../data/Wards_from_2012.geojson").json()
dc_roads = FileAttachment("../../data/major-roads.geojson").json()

crimeData = data_df.map(d => {
    d.report_date = new Date(d.report_date);
    return d;
});

// Plot DC map from geojson
marion_map = Plot.plot({
    width: 800,
    height: 800,
    title: "DC Car Thefts by Census Tract from 2019-2023",
    x: {axis: null},
    y: {axis: null},
    length: {range: [0, 100]},
    marks: [
        Plot.geo(dc, {fill: "#eee", stroke: "white", strokeWidth: 1}),
        Plot.geo(dc_roads, {stroke: "black", strokeWidth: 1}),
        Plot.spike(
            data_df,
            {
                x: "lon",
                y: "lat",
                length: "crimes",
                channels: {census_tract: "census_tract"},
                stroke: "#D34B7F"
            }
        ),
        Plot.tip(
            data_df,
            Plot.pointer({
                x: "lon", 
                y: "lat",
                channels: {census_tract: "census_tract", crimes: "crimes"},
                offset: 10,
                title: (d) => `Census Tract: ${d.census_tract}\n\nCar Thefts: ${d.crimes}`
            }
        )),
        legendSpike([50, 100, 150, 200, 250, 300], {stroke: "#D34B7F"})
    ]
})

function legendSpike(values, {frameAnchor = "bottom-right", format = "~s", stroke} = {}) {
  if (!Array.isArray(values)) values = Array.from(values);
  if (typeof format !== "function") format = d3.format(format);
  return Plot.marks(
    values.map((v, i) => {
      const dx = (i - values.length) * 18;
      return [
        Plot.spike([v], {
          length: [v],
          dx,
          dy: -20,
          frameAnchor,
          stroke
        }),
        Plot.text([v], {
          text: [format(v)],
          dx,
          dy: -10,
          frameAnchor,
          textAnchor: "middle"
        })
      ];
    })
  );
}

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Figure 6: DC car thefts are concentrated in downtown DC and the southeast quadrant. Source: Metropolitan Police Department Crime Incidents 2019-2023

Car Thefts by Ward in Washington, DC (2019-2023)

map = {
  const container = yield htl.html`<div style="height: 500px;">`;
  const map = L.map(container).setView([38.9072, -77.0369], 11);
  L.tileLayer("https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png", {
    attribution: "© <a href=https://www.openstreetmap.org/copyright>OpenStreetMap</a> contributors"
  }).addTo(map);

  L.geoJSON(dc_data, {
    style: function(feature) {
      return {color: colorScale(wardCounts[feature.properties.OBJECTID])};
    },
    onEachFeature: function (feature, layer) {
      layer.on('click', function () {
        const ward = this.feature.properties.OBJECTID;
        mutable selected_ward = ward;
      });
      // Add tooltip
      layer.bindTooltip(`Ward ${feature.properties.OBJECTID}: ${wardCounts[feature.properties.OBJECTID]} car thefts`);
    }
  }).addTo(map);
}
plot = Plot.plot({
  y: {
    grid: true,
  },
  marks: [
    Plot.ruleY([0]),
    Plot.barY(data, {x: "shift", y: "count"})
  ],
  title: `Shift Counts for Ward ${selected_ward}`
})

dc_data = d3.json("https://raw.githubusercontent.com/tsigall/5200-files/main/ACS_Demographic_Characteristics_DC_Ward.geojson")

arrest_data = d3.csv("https://raw.githubusercontent.com/tsigall/5200-files/main/crime_dc.csv")

mutable selected_ward = 1;

wardCounts = arrest_data.reduce((acc, d) => {
  acc[d.ward] = (acc[d.ward] || 0) + 1;
  return acc;
}, {});

colorScale = d3.scaleSequential()
  .domain([d3.max(Object.values(wardCounts)), 0])
  .interpolator(d3.interpolateMagma);

shiftCounts = arrest_data.filter(d => d.ward == selected_ward).reduce((acc, d) => {
  acc[d.shift] = (acc[d.shift] || 0) + 1;
  return acc;
}, {});

data = Object.entries(shiftCounts).map(([shift, count]) => ({shift, count}));

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Figure 7: Car thefts occur most frequently in the evening and overnight hours. Click on a ward to see the distribution of car thefts by shift. Source: Metropolitan Police Department Crime Incidents 2019-2023

Who is Committing These Crimes

We have seen where car thefts in DC are taking place, but now we want to look more at WHO is stealing cars in DC by taking a look at arrest data from 2019 to 2023. Before looking at car theft arrest data specifically, we first took a look at arrest data for ALL arrests that took place in this time period. In Figure 8, we can see that, on the whole, younger adults are way more inclined to be arrested than older adults. When looking at arrests for Unauthorized Use of a Vehicle (i.e., “joyriding”) and Theft First Degree (Stolen Auto), we can see that the proportion of those that were arrested that are younger is much higher than that of crimes like Unlawful Entry and Simple Assault. Motor vehicle theft is a younger man’s crime.

Figure 8: Car-theft related crimes are more common among younger individuals, while other crimes are more distributed across age groups. Source: Metropolitan Police Department Juvenile and Adult Arrests (2019 - 2023).

What about juveniles, though? Given the “Kia Boys” trend on Tik Tok, can we expect more juveniles to be committing crimes than adults? In Figure 9, we explore the proportion of adults that are arrested for different categories of crimes compared to juveniles. We can see that Unauthorized Use of a Vehicle is a crime that is committed by more juveniles than adults. While we cannot directly link social media like Tik Tok specifically to why those arrested for car thefts are younger, we do have some evidence to show that car theft is a crime that is popular among juveniles. It is certainly not far fetched to think that social media has increased the availability of knowledge on how to steal cars, like we have seen with the Kia Boys, which primarily is going to seen by juveniles.

Figure 9

When Are These Crimes Happening

Total DC Car Theft Activity by Hour of the Day for Each Year (2019-2023)

What times of the day are car thefts more likely to happen? Based on the data presented in Figure 10, it’s evident that there are distinct patterns in the timing of car thefts in Washington DC. The peak of thefts show to be happening between the hours of 12am-3am and 4pm-7pm. The reduced visibility and darkness, as well as less overall people activity during the early morning hours of 12am-3am provide favorable conditions for thieves to operate discreetly. Similarly, the spike in car thefts during the early evening hours, particularly between 4pm-7pm, can be correlated with factors such as the onset of darkness, increased vehicular traffic, and potential distractions as individuals return home from work or engage in other activities.

Figure 10: DC car thefts tend to occur more frequently during the late evening and early morning hours. The number of car thefts has increased overall, with the most significant increase occurring in 2023. Source: Metropolitan Police Department Crime Incidents 2019-2023.

Seeing where and when car theft in DC is taking place, along with who is primarily participating in car theft, we still are left with some questions on why car theft is going up. We do know that flaws in Kia and Hyundai manufacturing have made car theft more accessible to people, along with increased saliency on social media, but does this really explain at all? We were curious as to what else was driving car thefts up in DC, and upon initial research, while many experts attribute the increase heavily towards the Kia and Hyundai problem, a lot of it can be attributed to the DC Police struggling to arrest suspects for all motor vehicle theft cases they see (Iannelli 2024). In the below figure, we can notice that arrest counts for all crimes in DC have remained relatively the same while car thefts have continued to rise. DC police have not been able to keep up with all of the car thefts that have been happening in more recent years. This phenomenon perpetuates a feedback loop where car thefts realize the consequences of their crimes are not as likely to be met with swift justice, only encouraging further car theft. DC police have realized these circumstances and now have begun to incorporate more tactics in catching car thefts, but only time and new data will tell if these techniques are working (Khalil 2023).

Why Are These Crimes Happening

d3 = require("d3@7")

df = transpose(joiner_long)
    .map((d, i) => ({...d, Month: new Date(d.Month)}))

// create line chart with the data
Plot.plot({
  y: {grid: true, tickFormat: d => `${d > 0 ? "+" : ""}${Math.round(d)}%`, label: "Percent Change"},
  x: {type: "time", tickFormat: "%b %Y", label: "Month"},
  title_font: {size: 20, family: "Impact"},
  title: "Percent Change in Car Thefts and Related Arrests\nin DC from 2019 to 2023",
  // change the color of the lines with hex values
  color: {range: ["#D34B7F", "#493FB3", "#FFBF49"], legend: true},
  marks: [
    Plot.ruleY([0]),
    Plot.lineY(df, {x: "Month", y: "perc", stroke: "Type"}),
    Plot.tip(df, Plot.pointer({
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        y: "perc",
        color: "Type",
        title: d => `${d.Type}: ${d3.format("+.1f")(d.perc)}%`,
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  ],
  width: 1100,
  marginLeft: 100
})

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Figure 11: The percent change of juvenile arrests for car-related crimes has increased most significantly over the past five years. Car thefts have also increased significantly, while adult arrests have only slightly increased. Source: Metropolitan Police Department Crime Incidents, Adult Arrests, and Juvenile Arrests, 2019-2023.

Table 1: Counts and percent change of car thefts and car theft arrests in Washington, DC from 2019 to 2023. Source: Metropolitan Police Department and Open Data DC.

Car Thefts and Car Theft Arrests in Washington, DC
Theft and Arrests by Year
	2019	2020	2021	2022	2023	Timeline
Total Counts
Car Thefts	2,187	3,260	3,479	3,738	6,782
Car Theft Adult Arrests	430	451	407	367	507
Car Theft Juvenile Arrests	160	311	341	312	489
Percent Change from Jan. 2019
Car Thefts Percent Change	31.1%	95.4%	108.6%	124.1%	306.6%
Car Theft Adult Arrests Percent Change	43.3%	50.3%	35.7%	22.3%	69.0%
Car Theft Juvenile Arrests Percent Change	166.7%	418.3%	468.3%	420.0%	715.0%
Data from the Metropolitan Police Department and Open Data DC

In conclusion, the Kia and Hyundai theft epidemic has been a major factor in car theft rises in Washington DC. We explore how car thefts in DC are mostly taking place in historically economically disadvantaged communities and are primarily being committed by younger adults and juveniles. Arrest rates have also struggled to catch up with rising car theft rates, requiring DC police to adapt their strategies in catching car thieves. While it is hard to directly quantify how social media trends have impacted car theft rates, we do have pretty strong evidence to say social media has played a large role in providing access to car theft techniques, which can be observed through the skyrocketing proportion of stolen cars that are Hyundais or Kias in both DC and the country as whole. With recent class action lawsuits and calls by law enforcement officials and politicians for Kia and Hyundai to be held responsible for upticks in car thefts, we were directly able to observe this unique phenomenon in our community.

References

Arango, Tim, and Jacey Fortin. 2023. “Teens Are Stealing More Cars. They Learn How on Social Media.” The New York Times, March. https://www.nytimes.com/2023/03/10/us/car-thefts-kia-challenge-tiktok.html.

Balter, Ben. 2024. “dc-maps: Maps of Washington DC area public geodata.” https://github.com/benbalter/dc-maps.

Goldie, James. 2023. “quarto-experiments: A collection of Quarto experiments.” https://github.com/jimjam-slam/quarto-experiments.

Iannelli, Nick. 2024. “DC and Maryland top the nation in vehicle theft increases.” WTOP News. https://wtop.com/local/2024/04/dc-and-maryland-top-the-nation-in-vehicle-theft-increases/.

Khalil, Ashraf. 2023. “The District of Columbia is combating car thefts and carjackings with dashcams and AirTags.” The Associated Press. https://apnews.com/article/car-theft-carjacking-washington-dc-crime-68a081ec948898ab28b2bbb1018b8eb9.

Manjoo, Farhad. 2023. “Kia and Hyundai Helped Enable a Crime Wave. They Should Pay for It.” The New York Times, September. https://www.nytimes.com/2023/09/01/opinion/kia-hyundai-tiktok.html.

Metropolitan Police Department. 2024a. “Arrests by Year 2019.” https://mpdc.dc.gov/sites/default/files/dc/sites/mpdc/publication/attachments/Arrests%20by%20Year%2C%202019.csv; Government of the District of Columbia.

———. 2024b. “Arrests by Year 2020.” https://mpdc.dc.gov/sites/default/files/dc/sites/mpdc/publication/attachments/Arrests%20by%20Year%202020.csv; Government of the District of Columbia.

———. 2024c. “Arrests by Year 2021.” https://mpdc.dc.gov/sites/default/files/dc/sites/mpdc/publication/attachments/2021%20Adult%20Arrests%20for%20Open%20Data%2020220202.xlsx; Government of the District of Columbia.

———. 2024d. “Arrests by Year 2022.” https://mpdc.dc.gov/sites/default/files/dc/sites/mpdc/publication/attachments/2022%20adult%20arrests%20for%20open%20data.xlsx; Government of the District of Columbia.

———. 2024e. “Arrests by Year 2023.” https://mpdc.dc.gov/sites/default/files/dc/sites/mpdc/publication/attachments/2023%20adult%20arrests%20for%20open%20data_0.csv; Government of the District of Columbia.

———. 2024f. “Binannual Report 2019 Jan-June.” https://mpdc.dc.gov/node/1444396; Government of the District of Columbia.

———. 2024g. “Binannual Report 2019 July-Dec.” https://mpdc.dc.gov/node/1486931; Government of the District of Columbia.

———. 2024h. “Binannual Report 2020 Jan-June.” https://mpdc.dc.gov/node/1488966; Government of the District of Columbia.

———. 2024i. “Binannual Report 2020 July-Dec.” https://mpdc.dc.gov/node/1519206; Government of the District of Columbia.

———. 2024j. “Binannual Report 2021 Jan-June.” https://mpdc.dc.gov/node/1561311; Government of the District of Columbia.

———. 2024k. “Binannual Report 2021 July-Dec.” https://mpdc.dc.gov/node/1582166; Government of the District of Columbia.

———. 2024l. “Binannual Report 2022 Jan-June.” https://mpdc.dc.gov/node/1649861; Government of the District of Columbia.

———. 2024m. “Binannual Report 2022 July-Dec.” https://mpdc.dc.gov/node/1649856; Government of the District of Columbia.

———. 2024n. “Binannual Report 2023 Jan-June.” https://mpdc.dc.gov/node/1677791; Government of the District of Columbia.

———. 2024o. “Binannual Report 2023 July-Dec.” https://mpdc.dc.gov/node/1704896; Government of the District of Columbia.

Open Data DC. 2024a. “ACS 5-Year Demographic Characteristics DC Ward.” https://opendata.dc.gov/datasets/058207022b5a4b57b593247178d9b42e_39/about; Government of the District of Columbia.

———. 2024b. “Crime Incidents in 2019.” https://opendata.dc.gov/datasets/DCGIS::crime-incidents-in-2019/about; Government of the District of Columbia.

———. 2024c. “Crime Incidents in 2020.” https://opendata.dc.gov/datasets/DCGIS::crime-incidents-in-2020/about; Government of the District of Columbia.

———. 2024d. “Crime Incidents in 2022.” https://opendata.dc.gov/datasets/DCGIS::crime-incidents-in-2022/about; Government of the District of Columbia.

———. 2024e. “Crime Incidents in 2023.” https://opendata.dc.gov/datasets/DCGIS::crime-incidents-in-2023/about; Government of the District of Columbia.

———. 2024f. “Wards From 2012.” https://opendata.dc.gov/datasets/DCGIS::wards-from-2012/about; Government of the District of Columbia.

Paul, Shilpi. 2013. “Where Are DC’s Richest and Poorest Neighborhoods?” Urban Turf. https://dc.urbanturf.com/articles/blog/where_are_dcs_richest_and_poorest_neighborhoods/6478.

Valdes-Dapena, Peter. 2024. CNN Business. https://www.cnn.com/2024/01/04/business/hyundai-kia-thefts-increased-10-fold/index.html.